General statistical methods (STA903)

Depending on the composition of the PhD candidate group, the following topics will be covered with varying degree of depth: statistical inference theory, asymptotic theory, computational statistical methods, robust estimation and non-parametric methods. Further, selected topics in time series analysis, stochastic processes, survival analysis, spatial statistics or statistical methods on manifolds.


Course description for study year 2024-2025. Please note that changes may occur.

Facts

Course code

STA903

Version

1

Credits (ECTS)

10

Semester tution start

Spring, Autumn

Number of semesters

1

Exam semester

Spring, Autumn

Language of instruction

English, Norwegian

Content

Depending on the composition of the PhD candidate group, the following topics will be covered with varying degree of depth: statistical inference theory, asymptotic theory, computational statistical methods, robust estimation and non-parametric methods. Further, selected topics in time series analysis, stochastic processes, survival analysis, spatial statistics or statistical methods on manifolds.

Learning outcome

After completing the course, the candidate should have acquired knowledge regarding central concepts and ideas within advanced statistical theory and applications of such theory. The candidate should be able to apply such knowledge to understand advanced statistical texts and as a tool in their own research.

Required prerequisite knowledge

None

Recommended prerequisites

A master's degree in statistics, or a related subject which includes a variety of statistics courses.

Exam

Form of assessment Weight Duration Marks Aid
Oral exam 1/1 Passed / Not Passed

Course teacher(s)

Course teacher:

Tore Selland Kleppe

Course teacher:

Jörn Schulz

Course coordinator:

Tore Selland Kleppe

Course teacher:

Jan Terje Kvaløy

Course coordinator:

Jan Terje Kvaløy

Head of Department:

Bjørn Henrik Auestad

Method of work

Lectures and guided self-study.

Open for

Technology and Natural Science - PhD programme

Course assessment

There must be an early dialogue between the course supervisor, the student union representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital subject evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.

Literature

Search for literature in Leganto